Predicting the behaviors of other road users is crucial to safe and intelligent decision-making
for autonomous vehicles (AVs). However, most motion prediction models ignore the …

Autonomous driving vehicles can reduce congestion and improve safety while increasing
traffic efficiency. To reflect the quality of driving more comprehensively, the driving safety …

Predicting the behaviors of other agents on the road is critical for autonomous driving to
ensure safety and efficiency. However, the challenging part is how to represent the social …

It is critical to predict the motion of surrounding vehicles for self-driving planning, especially
in a socially compliant and flexible way. However, future prediction is challenging due to the …

How to make precise multi-agent trajectory prediction is a crucial problem in the context of
autonomous driving. It is significant to have the ability to predict surrounding road …

Predicting trajectories of multiple agents in interactive driving scenarios such as
intersections, and roundabouts are challenging due to the high density of agents, varying …

The reasonable trajectory prediction of surrounding traffic participants is crucial for
autonomous driving. Especially, how to predict multiple plausible trajectories is still a …

Precisely modeling interactions and accurately predicting trajectories of surrounding
vehicles are essential to the decision-making and path-planning of intelligent vehicles. This …

The abilities to understand the social interaction behaviors between a vehicle and its
surroundings while predicting its trajectory in an urban environment are critical for road …

Trajectory prediction of the ego vehicle is necessary for the cooperation driving of intelligent
vehicles and drivers. Methods based on deep learning can fit complex functions, but they …